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Tag: model behavior

  • Hacker News: How outdated information hides in LLM token generation probabilities

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    Kurt Seifried
    in

    Source URL: https://blog.anj.ai/2025/01/llm-token-generation-probabilities.html Source: Hacker News Title: How outdated information hides in LLM token generation probabilities Feedly Summary: Comments AI Summary and Description: Yes ### Summary: The text provides a deep examination of how large language models (LLMs), such as ChatGPT, process and generate responses based on conflicting and outdated information sourced from the internet.…

  • Cloud Blog: Supervised Fine Tuning for Gemini: A best practices guide

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    Kurt Seifried
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    Source URL: https://cloud.google.com/blog/products/ai-machine-learning/master-gemini-sft/ Source: Cloud Blog Title: Supervised Fine Tuning for Gemini: A best practices guide Feedly Summary: Foundation models such as Gemini have revolutionized how we work, but sometimes they need guidance to excel at specific business tasks. Perhaps their answers are too long, or their summaries miss the mark. That’s where supervised fine-tuning…

  • Simon Willison’s Weblog: Quoting Colin Fraser

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    system automation
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    Source URL: https://simonwillison.net/2025/Jan/4/colin-fraser/#atom-everything Source: Simon Willison’s Weblog Title: Quoting Colin Fraser Feedly Summary: Claude is not a real guy. Claude is a character in the stories that an LLM has been programmed to write. Just to give it a distinct name, let’s call the LLM “the Shoggoth". When you have a conversation with Claude, what’s…

  • Hacker News: Experiment with LLMs and Random Walk on a Grid

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    system automation
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    Source URL: https://github.com/attentionmech/TILDNN/blob/main/articles/2024-12-22/A00002.md Source: Hacker News Title: Experiment with LLMs and Random Walk on a Grid Feedly Summary: Comments AI Summary and Description: Yes **Summary:** The text describes an experimental exploration of the random walk behavior of various language models, specifically the gemma2:9b model compared to others. The author investigates the unexpected behavior of gemma2:9b,…

  • AlgorithmWatch: Large language models continue to be unreliable concerning elections

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    system automation
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    Source URL: https://algorithmwatch.org/en/llms_state_elections/ Source: AlgorithmWatch Title: Large language models continue to be unreliable concerning elections Feedly Summary: Large language models continue to be unreliable for election information. Our research was able to substantially improve the reliability of safeguards in the Microsoft Copilot chatbot against election misinformation in German. However barriers to data access greatly restricted…

  • Hacker News: Alibaba releases an ‘open’ challenger to OpenAI’s O1 reasoning model

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    system automation
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    Source URL: https://techcrunch.com/2024/11/27/alibaba-releases-an-open-challenger-to-openais-o1-reasoning-model/ Source: Hacker News Title: Alibaba releases an ‘open’ challenger to OpenAI’s O1 reasoning model Feedly Summary: Comments AI Summary and Description: Yes Summary: The arrival of the QwQ-32B-Preview model from Alibaba’s Qwen team introduces a significant competitor to OpenAI’s offerings in the AI reasoning space. With its innovative self-fact-checking capabilities and ability…

  • Hacker News: An Intuitive Explanation of Sparse Autoencoders for LLM Interpretability

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    system automation
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    Source URL: https://adamkarvonen.github.io/machine_learning/2024/06/11/sae-intuitions.html Source: Hacker News Title: An Intuitive Explanation of Sparse Autoencoders for LLM Interpretability Feedly Summary: Comments AI Summary and Description: Yes **Summary**: The text discusses Sparse Autoencoders (SAEs) and their significance in interpreting machine learning models, particularly large language models (LLMs). It explains how SAEs can provide insights into the functioning of…